DaedalMap World Development Indicators

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint=true, so description is not required to restate it. The description adds no behavioral traits beyond annotations; 'Free discovery' is marketing fluff.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise with two short sentences. No unnecessary words except possibly 'Free discovery', but overall efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and no output schema, the description adequately communicates the return value. Lacks details on pagination or limits, but for a simple listing tool it suffices.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, and schema coverage is 100%. Baseline score of 4 is appropriate as description does not need to add parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns a list of data packs on DaedalMap, using specific verb 'returns' and resource 'live agent-ready data packs'. However, it does not explicitly differentiate from siblings like get_pack or query_dataset, though the scope is implied.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as get_pack or query_dataset. The description lacks context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description is consistent with the readOnlyHint annotation, describing a read-only operation that returns metadata. It adds context about what is returned (coverage, freshness, etc.) beyond the annotation, but does not disclose any additional behavioral traits beyond that.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose and deliverables, then usage context. No redundant words. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one required parameter, no output schema, read-only), the description covers essential information: what it returns, when to call it, and its value. No missing details that would hinder an agent's decision to use this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameter pack_id is fully documented in the schema. The description mentions examples of pack_id values, but this largely repeats the schema's own examples without adding new semantic meaning. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns detailed metadata, coverage, freshness, guidance, and examples for one pack, specifying the verb (returns) and resource (one pack). It distinguishes from siblings by implying this is for a single pack's metadata, while siblings like get_catalog likely list packs and query_dataset queries data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises calling this before querying a new pack, providing clear context for when to use it. It explains the benefits (time shape, coverage limits, first query). However, it does not explicitly mention when not to use it or compare to alternatives like get_catalog or query_dataset.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint=true. Description adds meaningful behavioral context: references the specific API endpoint (POST /api/v1/query/dataset) and discloses which packs incur costs, helping the agent understand side effects and constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences: first defines purpose, second lists pack pricing. No fluff, front-loaded, efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite 100% schema coverage, the description lacks explanation of return format, mutual exclusivity of source_id/pack_id, and default behavior when no parameters provided. With no output schema, more detail on response would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 8 parameters have descriptions in the input schema (100% coverage), so baseline is 3. The tool description does not add additional parameter details beyond listing some pack values, which is already covered in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clear definition: 'Generic structured query for direct source_id or pack_id access' specifies verb (query) and resource (dataset). Distinguishes from siblings (get_catalog, get_pack) by focusing on direct data access.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides context on free vs paid packs, which guides which packs can be queried. However, no explicit guidance on when to use this tool over siblings (e.g., 'use for data retrieval, not listing catalogs').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.